CN114169642A - Predictive maintenance method and system applied to photovoltaic system and storage medium - Google Patents
Predictive maintenance method and system applied to photovoltaic system and storage medium Download PDFInfo
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Abstract
The invention belongs to the field of photovoltaic systems, and particularly relates to a predictive maintenance method, a predictive maintenance system and a storage medium for a photovoltaic system, wherein the method comprises the following steps: acquiring equipment information of a photovoltaic system, and generating a database; according to the acquired equipment information, combining with a preset predictive maintenance analysis strategy, automatically performing predictive maintenance analysis to generate an analysis result; extracting key information of photovoltaic system maintenance according to the analysis result, asking a user for authorization to obtain a user mobile phone serial number, simulating browsing data of the user about photovoltaic system maintenance learning through a virtual machine, and synchronizing the browsing data to the user mobile phone. The invention can solve the problem that the problems caused by improper daily maintenance or improper operation of a user cannot be reduced in the related maintenance mode in the prior art.
Description
Technical Field
The invention belongs to the field of photovoltaic systems, and particularly relates to a predictive maintenance method and system applied to a photovoltaic system and a storage medium.
Background
The photovoltaic system is also called as a solar photovoltaic power generation system and mainly comprises a photovoltaic module, a controller, an inverter, a storage battery and other accessories, and the solar photovoltaic power generation system is divided into an off-grid system and a grid-connected system according to whether the solar photovoltaic power generation system depends on a public power grid or not, wherein the off-grid system operates independently and does not depend on the power grid; the off-grid photovoltaic system is provided with a storage battery with an energy storage function, so that the power stability of the system can be ensured, and the power can be supplied to a load for power utilization under the condition that the photovoltaic system does not generate power at night or generates power insufficiently in rainy days; and no matter the off-grid photovoltaic system or the grid-connected photovoltaic system, regular maintenance is needed to ensure the service life of the photovoltaic system.
In the prior art, generally, operation and maintenance personnel regularly check a photovoltaic system of a user house, equipment replacement or part replacement is performed on a part of the photovoltaic system which is prone to causing a problem, a mode of manual regular check does not have a prediction function, and meanwhile, the situation that a user loses due to untimely maintenance occurs; in addition, adopt wisdom fortune dimension among the part correlation technique, mainly for the operational aspect through each equipment of supervisory equipment real time monitoring photovoltaic system in each subassembly, in time upload the management center platform with the problem point when the problem appears to be maintained by fortune dimension personnel, it can solve general maintenance problem, but the condition that has the photovoltaic system problem because user's misuse or daily maintenance improper cause takes place, this wisdom fortune dimension scheme can not reduce this type of condition and appears.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a predictive maintenance method, a predictive maintenance system and a storage medium applied to a photovoltaic system, so as to solve the problem that the problems caused by improper daily maintenance or improper operation of a user cannot be reduced in the related maintenance mode in the prior art.
The invention provides a basic scheme I: a predictive maintenance method for a photovoltaic system, comprising:
acquiring equipment information of a photovoltaic system, and generating a database;
according to the acquired equipment information, combining with a preset predictive maintenance analysis strategy, automatically performing predictive maintenance analysis to generate an analysis result;
extracting key information of photovoltaic system maintenance according to the analysis result, asking a user for authorization to obtain a user mobile phone serial number, simulating browsing data of the user about photovoltaic system maintenance learning through a virtual machine, and synchronizing the browsing data to the user mobile phone.
The principle and the advantages of the first basic scheme provided by the invention are as follows: in the related art, the operation condition of the photovoltaic system is monitored through the monitoring equipment, the management center platform is uploaded in time when problems occur, and maintenance is carried out by related operation and maintenance personnel, but in the problems of the photovoltaic system, besides the equipment problems caused by equipment line aging and environmental parameters, the problems caused by improper daily maintenance or improper use of a user also exist, and the problems are not solved by the related art.
Therefore, in order to solve the problems in the related art, the method comprises the steps of firstly collecting equipment information of the photovoltaic system, then storing the equipment information into the database, performing predictive maintenance analysis on the data stored in the database, and extracting key information about operation and maintenance of the photovoltaic system according to an analysis result, wherein the key information comprises equipment problem points, equipment problem root causes and a maintenance scheme; the method comprises the steps of acquiring a mobile phone serial number of a user, transmitting extracted key information and the mobile phone serial number to a virtual machine, simulating that the user browses data related to operation and maintenance learning of the photovoltaic system by using a mobile phone through the virtual machine, transmitting the browsed data to the mobile phone of the user, and simulating the browsed data of the mobile phone of the user, wherein the characteristics are based on big data, so that the occurrence frequency of the operation and maintenance learning of the photovoltaic system is increased when the user browses webpages or videos by using the mobile phone daily, the knowledge of the user in the field of the photovoltaic system is enhanced subconsciously, the user can independently perform maintenance or correct operation when the user uses the photovoltaic system daily, and the problems of the photovoltaic system are reduced. Therefore, the method has the advantages that (1) the equipment information of the photovoltaic system can be monitored and acquired in real time, and predictive maintenance can be achieved when the photovoltaic system has problems, so that user loss is avoided; (2) the use of a user mobile phone is simulated through the virtual machine, so that the learning of the photovoltaic system related operation and maintenance knowledge of the user can be subconsciously enhanced, and further the illegal use of the photovoltaic system in daily use of the user is reduced.
Further, the equipment information comprises equipment data, equipment operation data and equipment service life duration, the equipment data comprises equipment image data and equipment connection data, and the equipment operation data comprises equipment joint connection information, equipment box information, equipment temperature information, equipment dust deposition information, equipment corrosion information and equipment connecting piece information.
Has the advantages that: the acquired equipment data can be used for constructing an equipment three-dimensional model, the equipment operation data can be used for performing predictive maintenance analysis, and the equipment service life duration can be used for judging the health condition of the equipment.
Further, the acquiring device information of the photovoltaic system and generating the database includes:
collecting joint connection information, equipment box information and equipment temperature information of each equipment of the photovoltaic system in real time, generating a collection result, and storing the collection result in a database;
monitoring dust deposition information, equipment corrosion information and equipment connecting piece information of each equipment of the photovoltaic system in real time through monitoring equipment, generating a monitoring result and storing the monitoring result in a database;
and storing the acquisition result and the monitoring result in the database into a redis cache library, generating an equipment operation database, and periodically deleting data in the equipment operation database according to a preset time threshold.
Has the advantages that: joint connection information, equipment box information and temperature information through collection equipment can reflect the problem of photovoltaic system at the circuit reverse side, and through real time monitoring equipment's deposition information, equipment corrosion information and equipment connecting piece information, can reflect the physical variable problem of equipment, in later storing the collection result with the monitoring result in the redis cache storehouse, the efficiency of reading is maintained in multiplicable predictability, and through regularly deleting cache data, can avoid the condition that the internal memory is not enough to appear in the redis cache storehouse.
Further, the acquiring device information of the photovoltaic system and generating the database further includes:
the method comprises the steps of obtaining equipment data of the photovoltaic system, extracting the equipment operation data in an equipment operation database, carrying out three-dimensional modeling according to the equipment data to obtain a virtual equipment model, and controlling the virtual equipment model to carry out virtual operation according to the equipment operation data.
Has the advantages that: the method and the system have the advantages that the three-dimensional modeling model is built according to the equipment data, the operation of the model is controlled according to the equipment operation data, and operation and maintenance personnel can conveniently analyze and process the model through visual display.
Further, the automatic predictive maintenance analysis according to the acquired device information in combination with a preset predictive maintenance analysis strategy, and the generating of the analysis result includes:
establishing a map relation between the analysis result and the service life of the equipment to generate a predictive maintenance analysis map;
and monitoring the structure of the equipment on the basis of the predictive maintenance analysis map, and judging the health condition of the equipment.
Has the advantages that: the method has the advantages that the map relation is established between the analysis result and the service life of the equipment, the time point of the equipment with problems or the detailed problem root can be reflected more visually, the problem can be solved by operation and maintenance personnel in a targeted mode, the equipment structure is monitored on the established predictive maintenance analysis map, and the health condition of the equipment can be well judged.
The invention provides a second basic scheme: the predictive maintenance system applied to the photovoltaic system comprises a server and a database, wherein the server comprises an information acquisition module, a predictive maintenance module, an extraction module, a virtual machine and a wireless communication module, and the information acquisition module is used for acquiring equipment information of the photovoltaic system and transmitting the equipment information to the database; the predictive maintenance module is used for automatically performing predictive maintenance analysis according to the acquired equipment information and the preset predictive maintenance analysis strategy to generate an analysis result; the extraction module is used for extracting the key information of the photovoltaic system maintenance in the analysis result and transmitting the extraction result to the virtual machine; the information acquisition module is further used for inquiring user authorization to acquire a user mobile phone serial number and transmitting the user mobile phone serial number to the virtual machine, the virtual machine is used for receiving the extraction result and the mobile phone serial number and simulating browsing data of a user about maintenance and learning of the photovoltaic system, and the wireless communication module is used for synchronizing the browsing data to the user mobile phone.
The principle and the advantages of the basic scheme II provided by the invention are as follows: in the related art, the operation condition of the photovoltaic system is monitored through the monitoring equipment, the management center platform is uploaded in time when problems occur, and maintenance is carried out by related operation and maintenance personnel, but in the problems of the photovoltaic system, except the equipment problems caused by equipment line aging and environmental parameters, the problems caused by improper maintenance or improper use of users are also included, and the problems are not solved by the related art.
Therefore, in order to solve the problems in the related art, the method comprises the steps of firstly obtaining equipment information of the photovoltaic system through an information obtaining module, then storing the equipment information into a database, carrying out predictive maintenance analysis on the data stored in the database through a predictive maintenance module, and extracting key information about operation and maintenance of the photovoltaic system according to the analysis result through an extracting module, wherein the key information comprises equipment problem points, equipment problem root causes and a maintenance scheme; meanwhile, the information acquisition module acquires a mobile phone serial number of a user, the extracted key information and the mobile phone serial number are transmitted to the virtual machine, the user is simulated by the virtual machine to browse data related to photovoltaic system operation and maintenance learning by using the mobile phone, the browsed data are transmitted to the user mobile phone by the wireless communication module, and the browsed data of the user mobile phone are simulated, so that the frequency of occurrence of the photovoltaic system operation and maintenance learning is increased when the user uses the mobile phone daily to browse webpages or browse videos, the knowledge of the user in the photovoltaic system field is subconsciously enhanced, the user can independently perform maintenance or correct operation when the user uses the photovoltaic system daily, and the problems of the photovoltaic system are reduced. Therefore, the method has the advantages that (1) the equipment information of the photovoltaic system can be monitored and acquired in real time, and predictive maintenance can be achieved when the photovoltaic system has problems, so that user loss is avoided; (2) the use of a user mobile phone is simulated through the virtual machine, so that the learning of the photovoltaic system related operation and maintenance knowledge of the user can be subconsciously enhanced, and further the illegal use of the photovoltaic system in daily use of the user is reduced.
Further, the equipment information comprises equipment data, equipment operation data and equipment service life duration, the equipment data comprises equipment image data and equipment connection data, and the equipment operation data comprises equipment joint connection information, equipment box information, equipment temperature information, equipment dust deposition information, equipment corrosion information and equipment connecting piece information.
Has the advantages that: the acquired equipment data can be used for constructing an equipment three-dimensional model, the equipment operation data can be used for performing predictive maintenance analysis, and the equipment service life duration can be used for judging the health condition of the equipment.
The system further comprises a redis cache library, wherein the information acquisition module comprises a real-time acquisition unit and a real-time monitoring unit, and the real-time acquisition unit is used for acquiring joint connection information, equipment box information and equipment temperature information of each piece of equipment of the photovoltaic system in real time, generating an acquisition result and storing the acquisition result in a database; the real-time monitoring unit is used for monitoring dust deposition information, equipment corrosion information and equipment connecting piece information of each equipment of the photovoltaic system in real time through monitoring equipment, generating a monitoring result and storing the monitoring result in a database; the device comprises a redis cache library, a device operation database and a monitoring unit, wherein the redis cache library is used for receiving acquisition results and monitoring results in the database and generating the device operation database, a deleting unit is arranged in the redis cache library and used for periodically deleting data in the device operation database according to a preset time threshold.
Has the advantages that: joint connection information, equipment box information and temperature information through real-time acquisition unit collection equipment, can reflect the problem of photovoltaic system at the circuit reverse side, and through real-time monitoring unit real-time monitoring equipment's deposition information, equipment corrosion information and equipment connecting piece information, can reflect the physical variable problem of equipment, in the retrieval cache bank with collection result and monitoring result storage value afterwards, the efficiency of multiplicable predictive maintenance reading, and through deleting the unit periodic deletion cache data, can avoid the insufficient condition of memory to appear in the retrieval cache bank.
The server further comprises a virtual modeling module, a predictive maintenance analysis map module and an equipment health judgment module, wherein the virtual modeling module is used for acquiring equipment data of the photovoltaic system, extracting equipment operation data in an equipment operation database, performing three-dimensional modeling according to the equipment data to obtain a virtual equipment model, and controlling the virtual equipment model to perform virtual operation according to the equipment operation data; the predictive maintenance analysis map module is used for establishing a map relation between an analysis result and the service life duration of the equipment to generate a predictive maintenance analysis map; the equipment health judgment module is used for monitoring the equipment structure according to the predictive maintenance analysis map and judging the health condition of the equipment.
Has the advantages that: the virtual modeling module establishes a three-dimensional modeling model according to the equipment data, controls the operation of the model according to the equipment operation data, and facilitates analysis and processing of operation and maintenance personnel through visual and visual display; the predictive maintenance analysis map module establishes a map relation between an analysis result and the service life of the equipment, so that the time point of the equipment with a problem or the detailed root of the problem can be reflected more visually, the problem can be solved in a targeted manner by operation and maintenance personnel, and on the established predictive maintenance analysis map, the equipment health judgment module monitors the equipment structure, so that the health condition of the equipment can be well judged.
A predictive maintenance storage medium for a photovoltaic system, the storage medium having stored therein a predictive maintenance program for a photovoltaic system, the predictive maintenance program for a photovoltaic system when executed by a computer processor implementing a predictive maintenance method for a photovoltaic system as described above.
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FIG. 1 is a block flow diagram of an embodiment of the present invention;
fig. 2 is a schematic block diagram of an embodiment of the present invention.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention, while a logical order is shown in the embodiments, in some cases steps shown or described may be performed in an order different than that shown.
The following is further detailed by way of specific embodiments:
the embodiment is basically as shown in the attached figure 1: a predictive maintenance method for a photovoltaic system, comprising:
the method comprises the following steps: and acquiring equipment information of the photovoltaic system, and generating a database.
In the first step, the device information includes device data, device operation data, and device lifetime duration, where the device data includes device image data and device connection data, and specifically, the device image data is an outline image of a device in a photovoltaic system, for example, for a photovoltaic module, including a type of the photovoltaic module, the device image data belongs to monocrystalline silicon, polycrystalline silicon, or amorphous silicon, and for each type of the photovoltaic module, the device image data further includes a photoelectric conversion rate and a manufacturing process of the type, for example, for the monocrystalline silicon, the photoelectric conversion rate is about 18%, the manufacturing process is to use glass and waterproof resin for encapsulation, and the lifetime duration of the device is also included, for example, the lifetime of the monocrystalline silicon is 25 years; the more detailed the device data obtained in the present invention is, the more beneficial the operation and maintenance personnel to know about the device problem is.
The equipment operation data comprises equipment joint connection information, equipment box information, equipment temperature information, equipment dust deposition information, equipment corrosion information and equipment connecting piece information, wherein the equipment joint connection information is specifically the contact condition of an MC4 joint of the equipment and is used for checking whether the MC4 joint has heating and melting phenomena; the equipment box information is specifically used for checking the sealing performance of the junction box and the plugging condition of a cable hole in the junction box; the equipment temperature information is specifically used for detecting the temperature of each equipment of the photovoltaic system and checking whether temperature abnormality occurs, in this embodiment, the equipment connector connection information and the equipment temperature information can be detected through an infrared detector or infrared monitoring equipment, and the equipment box information can be detected through a temperature and humidity sensor; the equipment dust accumulation information is specifically that in a photovoltaic system, a photovoltaic module is located outdoors all the year round, dust is easily accumulated on the surface of the photovoltaic module, and the efficiency of the photovoltaic module for absorbing light energy is weakened, so that the equipment can be regularly checked through monitoring equipment; the equipment corrosion information is specifically that the photovoltaic system equipment is easily corroded by rainwater because the photovoltaic system equipment is exposed outdoors, so that whether the surface of a photovoltaic module is corroded or not and whether equipment connecting pieces and fixing pieces are corroded or not can be checked in a manual regular inspection mode; the equipment connecting piece information specifically includes that weather influence is easily received to the connecting piece between each equipment in the photovoltaic system, for example, the connecting piece of photovoltaic module is easy not hard up under the strong wind weather, causes the danger that equipment drops easily to take place, consequently needs the fixed condition of connection of check out equipment around the bad weather, but the condition that can not appear dropping.
The service life duration of the equipment refers to the estimated service life of the equipment since the equipment leaves a factory.
In this embodiment, the device data in the device information and the device service life duration acquisition source include an instruction manual, a maintenance manual, an installation drawing, and the like.
Thus, as described above, step one, acquiring equipment information of the photovoltaic system, generating the database includes:
collecting joint connection information, equipment box information and equipment temperature information of each equipment of the photovoltaic system in real time, generating a collection result, and storing the collection result in a database;
monitoring dust deposition information, equipment corrosion information and equipment connecting piece information of each equipment of the photovoltaic system in real time through monitoring equipment, generating a monitoring result and storing the monitoring result in a database;
and storing the acquisition result and the monitoring result in the database into a redis cache library, generating an equipment operation database, and periodically deleting data in the equipment operation database according to a preset time threshold.
In this embodiment, the acquisition result and the monitoring result in the database are stored in a redis cache library to generate a device running database, the speed of subsequent predictive maintenance analysis is increased by using the characteristic that the reading speed of the redis cache library is high, data in the device running database is periodically deleted according to a preset time threshold, and the memory load of the redis cache library is reduced, where the preset time threshold is 5 days in this embodiment.
In addition, acquiring equipment information of the photovoltaic system, and generating the database further comprises:
the method comprises the steps of obtaining equipment data of the photovoltaic system, extracting the equipment operation data in an equipment operation database, carrying out three-dimensional modeling according to the equipment data to obtain a virtual equipment model, and controlling the virtual equipment model to carry out virtual operation according to the equipment operation data.
In this embodiment, the acquired device data in the photovoltaic system is subjected to three-dimensional modeling to obtain a virtual device model, and the constructed virtual device model can be split and assembled, so that operation and maintenance personnel can perform autonomous analysis conveniently, the device structure and device problem root are mastered, the virtual device model is controlled to perform virtual operation according to the device operation data, and detailed labeling is performed on temperature information, connection information, circuit parameter information and the like of each device of the photovoltaic system in the virtual device model, so that the virtual device model is more intuitive.
Step two: and automatically performing predictive maintenance analysis according to the acquired equipment information and a preset predictive maintenance analysis strategy to generate an analysis result.
In the second step, an analysis strategy is preset, for example, the dust accumulation condition of the photovoltaic module is mainly monitored according to the dust accumulation information of the photovoltaic system, the photovoltaic module is placed outdoors, when dust falls on the surface of the photovoltaic module, the irradiation of light rays to the photovoltaic module is shielded, the effective area of the photovoltaic module which actually receives sunlight is reduced, and the transmission uniformity of part of incident light rays in the glass cover plate is changed, so that the analysis strategy is to establish a curve map about the voltage and the illumination intensity of the photovoltaic module, and reflect the dust accumulation condition of the photovoltaic module from the curve map.
And two steps of automatically performing predictive maintenance analysis according to a preset analysis strategy to generate an analysis result, wherein the second step comprises the following steps:
establishing a map relation between the analysis result and the service life of the equipment to generate a predictive maintenance analysis map;
and monitoring the structure of the equipment on the basis of the predictive maintenance analysis map, and judging the health condition of the equipment.
In this embodiment, through the concrete aspect that the equipment goes wrong in the analysis result, long when combining equipment life, establish the predictive maintenance analysis map, reflect the influence that the equipment caused to the life of equipment along with the appearance of problem, and then monitor in combination with the structure of equipment, judge the health status of equipment, consider whether need to change equipment and do technical analysis support for the fortune dimension personnel, avoid unnecessary equipment change and predict the inaccurate user property loss that causes to equipment life.
Step three: extracting key information of photovoltaic system maintenance according to the analysis result, asking a user for authorization to obtain a user mobile phone serial number, simulating browsing data of the user about photovoltaic system maintenance learning through a virtual machine, and synchronizing the browsing data to the user mobile phone.
In the embodiment, in order to enhance the awareness of the user to the daily maintenance of the photovoltaic system, by inquiring the user authorization to obtain the mobile phone serial number of the user, extracting key information about photovoltaic system maintenance in the analysis result, including equipment problem points, problem root causes, maintenance schemes and the like, transmitting the serial number and the key information of the user mobile phone to the virtual machine, performing browsing data simulation by the virtual machine according to the received data, wherein the browsing data is knowledge about daily maintenance and use of the photovoltaic system, the browsing data is transmitted to a mobile phone of a user, the frequency of relevant videos or webpage recommendations related to daily maintenance and use of the photovoltaic system is increased based on the definition of big data when a user browses and refreshes webpages daily, and then strengthen the knowledge about the photovoltaic system field of user through subconscious, very big reduction because of the equipment problem that user maloperation or maintenance improper caused appears.
As shown in fig. 2, in another embodiment of the present embodiment, the system further includes a predictive maintenance system applied to the photovoltaic system, the system includes a server, a database and a redis cache library, the server includes an information acquisition module, a predictive maintenance module, an extraction module, a virtual machine, a wireless communication module, a virtual modeling module, a predictive maintenance analysis map module and a device health judgment module, wherein:
the information acquisition module is used for acquiring equipment information of the photovoltaic system and transmitting the equipment information to the database; the equipment information comprises equipment data, equipment operation data and equipment service life duration, wherein the equipment data comprises equipment image data and equipment connection data, and the equipment operation data comprises equipment joint connection information, equipment box information, equipment temperature information, equipment dust deposition information, equipment corrosion information and equipment connecting piece information;
the information acquisition module comprises a real-time acquisition unit and a real-time monitoring unit, wherein the real-time acquisition unit is used for acquiring joint connection information, equipment box information and equipment temperature information of each equipment of the photovoltaic system in real time, generating an acquisition result and storing the acquisition result in a database; the real-time monitoring unit is used for monitoring dust deposition information, equipment corrosion information and equipment connecting piece information of each equipment of the photovoltaic system in real time through the monitoring equipment, generating a monitoring result and storing the monitoring result in the database;
the redis cache library is used for receiving the acquisition result and the monitoring result in the database and generating an equipment operation database, and is provided with a deleting unit which is used for periodically deleting data in the equipment operation database according to a preset time threshold; the virtual modeling module is used for acquiring equipment data of the photovoltaic system, extracting equipment operation data in an equipment operation database, performing three-dimensional modeling according to the equipment data to obtain a virtual equipment model, and controlling the virtual equipment model to perform virtual operation according to the equipment operation data;
the predictive maintenance module is used for automatically performing predictive maintenance analysis according to the acquired equipment information and the preset predictive maintenance analysis strategy to generate an analysis result;
the predictive maintenance analysis map module is used for establishing a map relation between the analysis result and the service life of the equipment to generate a predictive maintenance analysis map;
the equipment health judgment module is used for monitoring the equipment structure according to the predictive maintenance analysis map and judging the health condition of the equipment;
the extraction module is used for extracting the key information of the photovoltaic system maintenance in the analysis result and transmitting the extraction result to the virtual machine;
the information acquisition module is also used for inquiring user authorization to acquire a user mobile phone serial number and transmitting the user mobile phone serial number to the virtual machine, and the virtual machine is used for receiving the extraction result and the mobile phone serial number and simulating browsing data of a user about maintenance and learning of the photovoltaic system;
the wireless communication module is used for synchronizing the browsing data to the mobile phone of the user.
In another embodiment of the present embodiment, the method further includes a predictive maintenance storage medium applied to the photovoltaic system, the storage medium storing therein a predictive maintenance program applied to the photovoltaic system, the predictive maintenance program applied to the photovoltaic system being executed by a computer processor to implement the steps of the predictive maintenance method applied to the photovoltaic system as described above.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. The term "comprising", without further limitation, means that the element so defined is not excluded from the group of processes, methods, articles, or systems that include the element.
The foregoing are merely exemplary embodiments of the present invention, and no attempt is made to show structural details of the invention in more detail than is necessary for the fundamental understanding of the art, the description taken with the drawings making apparent to those skilled in the art how the several forms of the invention may be embodied in practice with the teachings of the invention. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (10)
1. The predictive maintenance method applied to the photovoltaic system is characterized in that: the method comprises the following steps:
acquiring equipment information of a photovoltaic system, and generating a database;
according to the acquired equipment information, combining with a preset predictive maintenance analysis strategy, automatically performing predictive maintenance analysis to generate an analysis result;
extracting key information of photovoltaic system maintenance according to the analysis result, asking a user for authorization to obtain a user mobile phone serial number, simulating browsing data of the user about photovoltaic system maintenance learning through a virtual machine, and synchronizing the browsing data to the user mobile phone.
2. The predictive maintenance method applied to photovoltaic systems according to claim 1, characterized in that: the equipment information comprises equipment data, equipment operation data and equipment service life duration, the equipment data comprises equipment image data and equipment connection data, and the equipment operation data comprises equipment joint connection information, equipment box information, equipment temperature information, equipment dust deposition information, equipment corrosion information and equipment connecting piece information.
3. The predictive maintenance method applied to photovoltaic systems according to claim 2, characterized in that: the acquiring equipment information of the photovoltaic system and generating a database comprises:
collecting joint connection information, equipment box information and equipment temperature information of each equipment of the photovoltaic system in real time, generating a collection result, and storing the collection result in a database;
monitoring dust deposition information, equipment corrosion information and equipment connecting piece information of each equipment of the photovoltaic system in real time through monitoring equipment, generating a monitoring result and storing the monitoring result in a database;
and storing the acquisition result and the monitoring result in the database into a redis cache library, generating an equipment operation database, and periodically deleting data in the equipment operation database according to a preset time threshold.
4. The predictive maintenance method applied to photovoltaic systems according to claim 3, characterized in that: the acquiring of the device information of the photovoltaic system and the generating of the database further include:
the method comprises the steps of obtaining equipment data of the photovoltaic system, extracting the equipment operation data in an equipment operation database, carrying out three-dimensional modeling according to the equipment data to obtain a virtual equipment model, and controlling the virtual equipment model to carry out virtual operation according to the equipment operation data.
5. The predictive maintenance method applied to photovoltaic systems according to claim 4, characterized in that: the automatic predictive maintenance analysis is performed according to the acquired equipment information and in combination with a preset predictive maintenance analysis strategy, and the analysis result generation comprises the following steps:
establishing a map relation between the analysis result and the service life of the equipment to generate a predictive maintenance analysis map;
and monitoring the structure of the equipment on the basis of the predictive maintenance analysis map, and judging the health condition of the equipment.
6. Predictive maintenance system for photovoltaic systems, characterized in that: the photovoltaic system information acquisition system comprises a server and a database, wherein the server comprises an information acquisition module, a predictive maintenance module, an extraction module, a virtual machine and a wireless communication module, and the information acquisition module is used for acquiring equipment information of a photovoltaic system and transmitting the equipment information to the database; the predictive maintenance module is used for automatically performing predictive maintenance analysis according to the acquired equipment information and the preset predictive maintenance analysis strategy to generate an analysis result; the extraction module is used for extracting the key information of the photovoltaic system maintenance in the analysis result and transmitting the extraction result to the virtual machine; the information acquisition module is further used for inquiring user authorization to acquire a user mobile phone serial number and transmitting the user mobile phone serial number to the virtual machine, the virtual machine is used for receiving the extraction result and the mobile phone serial number and simulating browsing data of a user about maintenance and learning of the photovoltaic system, and the wireless communication module is used for synchronizing the browsing data to the user mobile phone.
7. The predictive maintenance system for photovoltaic systems of claim 6, wherein: the equipment information comprises equipment data, equipment operation data and equipment service life duration, the equipment data comprises equipment image data and equipment connection data, and the equipment operation data comprises equipment joint connection information, equipment box information, equipment temperature information, equipment dust deposition information, equipment corrosion information and equipment connecting piece information.
8. The predictive maintenance system for photovoltaic systems of claim 7, wherein: the system also comprises a redis cache library, wherein the information acquisition module comprises a real-time acquisition unit and a real-time monitoring unit, and the real-time acquisition unit is used for acquiring joint connection information, equipment box information and equipment temperature information of each piece of equipment of the photovoltaic system in real time, generating an acquisition result and storing the acquisition result in the database; the real-time monitoring unit is used for monitoring dust deposition information, equipment corrosion information and equipment connecting piece information of each equipment of the photovoltaic system in real time through monitoring equipment, generating a monitoring result and storing the monitoring result in a database; the device comprises a redis cache library, a device operation database and a monitoring unit, wherein the redis cache library is used for receiving acquisition results and monitoring results in the database and generating the device operation database, a deleting unit is arranged in the redis cache library and used for periodically deleting data in the device operation database according to a preset time threshold.
9. The predictive maintenance system for photovoltaic systems of claim 8, wherein: the server also comprises a virtual modeling module, a predictive maintenance analysis map module and an equipment health judgment module, wherein the virtual modeling module is used for acquiring equipment data of the photovoltaic system, extracting equipment operation data in an equipment operation database, performing three-dimensional modeling according to the equipment data to obtain a virtual equipment model, and controlling the virtual equipment model to perform virtual operation according to the equipment operation data; the predictive maintenance analysis map module is used for establishing a map relation between an analysis result and the service life duration of the equipment to generate a predictive maintenance analysis map; the equipment health judgment module is used for monitoring the equipment structure according to the predictive maintenance analysis map and judging the health condition of the equipment.
10. Predictive maintenance storage medium for photovoltaic systems, characterized in that: the storage medium stores a predictive maintenance program applied to the photovoltaic system, which when executed by a computer processor implements the predictive maintenance method applied to the photovoltaic system according to any one of claims 1 to 5.
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